ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

BACKGROUND: Durvalumab after chemoradiotherapy (CRT) failed to bring survival benefits to patients with epidermal growth factor receptor ( EGFR ) mutations in PACIFIC study (evaluating durvalumab in patients with stage III, unresectable NSCLC who did not have disease progression after concurrent chemoradiotherapy). We aimed to explore whether locally advanced inoperable patients with EGFR mutations benefit from tyrosine kinase inhibitors (TKIs) and the optimal treatment regimen. METHODS: We searched the PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases from inception to December 31, 2022 and performed a meta-analysis based on a Bayesian framework, with progression-free survival (PFS) and overall survival (OS) as the primary endpoints. RESULTS: A total of 1156 patients were identified in 16 studies that included 6 treatment measures, including CRT, CRT followed by durvalumab (CRT-Durva), TKI monotherapy, radiotherapy combined with TKI (RT-TKI), CRT combined with TKI (CRT-TKI), and TKI combined with durvalumab (TKI-Durva). The PFS of patients treated with TKI-containing regimens was significantly longer than that of patients treated with TKI-free regimens (hazard ratio [HR] = 0.37, 95% confidence interval [CI], 0.20-0.66). The PFS of TKI monotherapy was significantly longer than that of CRT (HR = 0.66, 95% CI, 0.50-0.87) but shorter than RT-TKI (HR = 1.78, 95% CI, 1.17-2.67). Furthermore, the PFS of RT-TKI or CRT-TKI were both significantly longer than that of CRT or CRT-Durva. RT-TKI ranked first in the Bayesian ranking, with the longest OS (60.8 months, 95% CI = 37.2-84.3 months) and the longest PFS (21.5 months, 95% CI, 15.4-27.5 months) in integrated analysis. CONCLUSIONS: For unresectable stage III EGFR mutant NSCLC, RT and TKI are both essential. Based on the current evidence, RT-TKI brings a superior survival advantage, while CRT-TKI needs further estimation. Large randomized clinical trials are urgently needed to explore the appropriate application sequences of TKI, radiotherapy, and chemotherapy. REGISTRATION PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42022298490.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; ErbB Receptors/genetics* ; Lung Neoplasms/drug therapy* ; Mutation/genetics* ; Protein Kinase Inhibitors/therapeutic use* ; Chemoradiotherapy ; Antibodies, Monoclonal/therapeutic use*

Trauma is the main cause of death and disability. Patients with severe trauma have hemorrhagic shock, traumatic coagulopathy and other diseases, which increase the risk of death. Platelets are important in the hemostatic response, but their function is rapidly dysregulated in trauma patients, leading to traumatic coagulopathy, blood loss, and early death. In addition to their role in hemostasis, platelets act as coordinators of the initial immune response, which can lead to immunothrombosis, organ dysfunction, and increased late mortality. At present, the treatment of post traumatic platelet dysfunction is mainly based on early hemostasis, and late prevention and treatment of thrombosis and organ dysfunction. In this review, the characteristics, underlying mechanisms, diagnosis and treatment strategies of platelet dysfunction in different periods are summarized, to provide ideas for studying the mechanism of platelet dysfunction after trauma and the treatment strategy for trauma patients.
Humans ; Wounds and Injuries/therapy* ; Blood Platelets/metabolism* ; Blood Platelet Disorders/etiology* ; Animals ; Hemostasis

OBJECTIVE: To investigate the prognostic value of peripheral blood absolute monocyte count(AMC) in non-severe aplastic anaemia(NSAA) patients. METHODS: 178 patients with NSAA who attended the Affiliated Hospital of Xuzhou Medical University from April 2008 to September 2020 were retrospectively analyzed, and the optimal cut-off value of peripheral blood AMC was determined by the receiver operating characteristic curve of the subjects, and they were divided into low AMC group (48 patients) and normal AMC group (130 patients), and the differences in clinical characteristics between the two groups were compared. Overall survival(OS) and progression-free survival(PFS) were analyzed by Kaplan-Meier. Univariate and multivariate Cox regression analysis were used to determine the independent prognostic value of AMC. RESULTS: Among 178 NSAA patients, 105(59.0%) were male and 73(41.0%) were female, with a median age of 31(18-87) years old, a median follow-up time of 58 months (range: 6 months-175 months), and a median AMC of 0.15×10⁹/L ［range: (0.01-0.59)×10⁹/L)］. The proportion of granulocytes (27.5% vs 36.0%, P < 0.05), and the proportion of mature monocytes (1% vs 2%, P < 0.05) in the low AMC group were lower than that in the normal AMC group; the proportion of mature lymphocytes in the low AMC group was higher than that in the normal AMC group (54% vs 50%, P < 0.05). However, there was no significantly different in the proportion of erythropoietic cells and stages of the erythropoietic cells between the two groups ( P >0.05). CR (27.7% vs 10.4%) and ORR (75.4% vs 56.3%) in the normal AMC group were higher than that in the low AMC group. Compared with patients in the low AMC group, AA patients in the normal AMC had better 5-year OS (98.5% vs 86.9%, P < 0.01), and the 5-year PFS (86.0% vs 58.9%, P < 0.01). Also, the 10-year survival rate of patients in the normal AMC group was higher than that in the low AMC group (98.5% vs 60.5%,P < 0.01). Univariate analysis showed that age, reticulocyte count, AMC<0.1×10⁹/L and the proportion of bone marrow mature monocytes were related with patients survival. Multivariate Cox regression analysis showed that monocyte count reduction was not an independent poor prognostic factor in NSAA patients （HR =4.474，95%CI ：0.508-44.390； P =0.172）. CONCLUSION Low AMC level at initial diagnosis is not an independent prognostic factor for NSAA patients, but still suggest potential prognostic value of AMC.
Humans ; Anemia, Aplastic/diagnosis* ; Female ; Male ; Prognosis ; Monocytes ; Adult ; Middle Aged ; Retrospective Studies ; Adolescent ; Aged ; Young Adult ; Aged, 80 and over ; Leukocyte Count

OBJECTIVE: To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation. METHODS: Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0. RESULTS: A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×10⁴ copies/ml, significantly higher than that in T cells (4.00×10³ copies/ml, P <0.01) and NK cells (2.85×10² copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days). CONCLUSION In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans ; Hematologic Neoplasms/virology* ; Herpesvirus 4, Human/physiology* ; Epstein-Barr Virus Infections ; Hematopoietic Stem Cell Transplantation ; Virus Activation ; Lymphocyte Subsets/virology* ; Flow Cytometry ; Killer Cells, Natural/virology* ; Male ; Female ; B-Lymphocytes/virology* ; Viral Load ; Adult ; T-Lymphocytes/virology* ; Middle Aged

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

OBJECTIVE: To elucidate the molecular mechanisms underlying sepsis-induced injury in mouse intestinal organoids and investigate the possible mechanisms or potential drug targets of myeloid differentiation factor 88 inhibitor [TJ-M2010-5 (TJ5)] on this condition. METHODS: Small intestinal organoids from C57BL/6 mice aged 6-8 weeks were established and characterized using immunofluorescence for cell growth and proliferation marker nuclear antigen Ki-67, goblet cell marker mucin-2 (MUC-2), epithelial cell marker E-cadherin, and Paneth cell marker lysozyme (Lyz). Small intestinal organoids after 3 days of passaging were divided into different groups: a normal control group treated with culture medium containing 0.2% dimethyl sulfoxide (DMSO) for 10 hours, a lipopolysaccharide (LPS) group treated with culture medium containing 200 mg/L LPS and 0.2% DMSO for 10 hours, and a TJ5 group pre-treated with 10 mmol/L TJ5 for 2 hours followed by treatment with culture medium containing 200 mg/L LPS for 10 hours. Real-time fluorescence quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to measure the expression levels of interleukin-6 (IL-6) and zonula occludens-1 (ZO-1) in the small intestinal organoids. RNA transcriptome sequencing was performed on the small intestinal organoids from each group to analyze differentially expressed genes between groups, and significant enrichment was analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: By the 7th day of primary culture, mature organoids had formed, and their growth rate increased after passaging. Immunofluorescence identification showed expressions of Ki-67, MUC-2, E-cadherin, and Lyz, indicating that the mouse small intestinal organoids maintained their cellular composition and functional characteristics under in vitro culture conditions. RT-qPCR results showed that compared with the normal control group, the mRNA expression of IL-6 in the small intestinal organoids of the LPS group was significantly increased (2^-ΔΔCT: 1.83±0.16 vs. 1.02±0.28, P < 0.05), while the mRNA expression of ZO-1 was significantly decreased (2^-ΔΔCT: 0.53±0.11 vs. 1.01±0.18, P < 0.05). In contrast, the mRNA expression trends of both IL-6 and ZO-1 were reversed in the TJ5 group, showing statistically significant differences as compared with the LPS group (2^-ΔΔCT: IL-6 mRNA was 1.24±0.01 vs. 1.83±0.16, ZO-1 mRNA was 1.97±0.29 vs. 0.53±0.11, both P < 0.05). RNA transcriptome sequencing showed 49 differentially expressed genes in the LPS group compared to the normal control group, with 42 upregulated and 7 downregulated. Compared to the LPS group, the TJ5 group showed 84 differentially expressed genes, with 47 upregulated and 37 downregulated. GO enrichment analysis of these differentially expressed genes showed that the significantly enriched biological processes of the differentially expressed genes between the normal control group and the LPS group included responses to LPS, responses to molecule of bacterial origin and responses to bacterium. The significantly enriched biological processes of the differentially expressed genes between the LPS group and the TJ5 group included glutathione metabolic processes, responses to stress cellular and responses to chemical stimulus. In molecular function groups, glutathione binding and oligopeptide binding were significantly enriched by the differentially expressed genes. In cellular component classifications, the enrichment of the differentially expressed genes was mainly observed in the cytoplasm, endoplasmic reticulum, and microsomes. KEGG pathway enrichment analysis indicated that the differentially expressed genes between the normal control group and LPS group were enriched in IL-17 signaling pathways, tumor necrosis factor (TNF) signaling pathways, viral protein interactions with cytokines and cytokine receptors signaling pathways, and cytokine-cytokine receptor interaction signaling pathways. In contrast, the differentially expressed genes between the LPS and TJ5 groups were mainly enriched in atherosclerosis signaling pathways, ferroptosis signaling pathways, glutathione metabolism signaling pathways, and cytochrome P450-mediated drug metabolism signaling pathways. CONCLUSIONS Mouse small intestinal organoids were successfully extracted and cultured. TJ5 may exert its protective effects by regulating gene expression and related signaling pathways (fluid shear stress and atherosclerosis, ferroptosis, glutathione metabolism, cytochrome P450 drug metabolism, etc.) in sepsis-injured mouse small intestinal organoids. These genes and signaling pathways may be key targets for treating sepsis-induced intestinal injury.
Animals ; Mice ; Sepsis/genetics* ; Organoids/drug effects* ; Mice, Inbred C57BL ; Intestine, Small/metabolism* ; Gene Expression Profiling ; Transcriptome ; Lipopolysaccharides